xYAF: A metric to evaluate punt returns in the NFL

Ethan, Kilbourne, Michael

12/7/2021

Background - “Expected” metrics

Expected Yards After Fielding (xYAF)

Data

Model Evaluations

Linear Regression

Linear Regression

Linear Regression

Logistic Regression

Best Subset Selection (Forward, Backward)

Forward Subset Selection

Best Subset Selection (Forward, Backward)

Forward Variable Selection

Best Subset Selection (Forward, Backward)

Forward Variable Selection

Best Subset Selection (Forward, Backward)

Backward

Best Subset Selection (Forward, Backward)

Backward Variable Selection

Best Subset Selection (Forward, Backward)

Backward Variable Selection

Random Forests

Random Forests

Random Forests

LASSO/Ridge Regression

Actual vs Predicted Lasso

GAMs

GAM Model

GAM

Actual vs Predicted

Splines

Actual vs Predicted

Boosting

Actual vs Predicted

Model Comparison

MSEs

Evaluation and Conclusion

Evaluation

Problem: Some methods assume normally distributed data

Evaluation

Possible solution: Variable Transforms

Evaluation

Better, but also doesn’t handle negative values.

Examples

An 85 yard punt return by Diontae Johnson

Examples

A 2 yard punt return by Richie James Jr.

Works Cited

[1] Sam Green. Assessing the performance of Premier League goalscorers. Stats Perform, 2012.

[2] https://grantland.com/features/expected-value-possession-nba-analytics/

[3] https://www.nfl.com/news/next-gen-stats-intro-to-expected-yards-after-catch-0ap3000000983644

[4] Peng et. al., A Defensive Player Coverage Evaluation Framework, https://www.kaggle.com/model284/a-defensive-player-coverage-evaluation-framework